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According to TAVANIR company`s statistics, despite fulfilling the electricity supply plans to the villages with more than 20 families in rural areas of Iran, Still, more than 17,000 rural families in villages ,with populations less than 20 families, are deprived from accessing to the electricity. Production Losses, transmission and distribution of electricity and the distribution of the population cause use of solar energy in remote areas. Hence, photovoltaic systems, because of direct conversion of solar energy into electricity without the need for sophisticated equipment are important. In this paper, an economic evaluation of Off Grid photovoltaic systems against national power grid has been studied in Tehran villages, due to the uncertainty in modeling; Monte Carlo simulation with 2000 iterations was used. We did Economic evaluation, using the life cycle cost of a photovoltaic system for a period of 25 to 30 years as well as the development costs for the power grid to remote villages. The paper shows the minimum distance of the village distribution network that the photovoltaic system is more economical than the national power grid development. This distance has inverse relation with discount rate as well as direct relation with the number of cloudy days and the number of rural families.

Importance of renewable-energy resources because of scarcity, greenhouse-gas emissions, and their fundamental roles in production and sustainable development, has made governments to reduce energy consumption and improving energy efficiency. In this regard, targeting subsidies rule was running in Iran since 2010. Since energy additionaly to labor and capital is one of the important inputs in production, running this rule with increasing energy price, affects manufacturing industries due to the type of energy and industry. In this research, the impacts of price liberalization on electricity efficiency have evaluated. Partial adjustment model, generalized method of moment and energy intensity measure are applied to this purpose. Data are collected from Statistical Center of Iran during 1995-2013. The research innovations are: using a partial adjustment model in evaluating efficiency, assessment whole industrial groups, and the period of research. The results show that in 95 percent level of confidence, the Iranian manufacturing industries are significantly flexible for changing the use of electricity. But the electricity efficiency has gotten worse after running the rule. In general, apposite of expectations, targeting subsidies rule has failed to improve electricity efficiency at least in short run.

According to the importance of expanding the use of clean energy, especially solar energy, in this study a solar cooker was designed, built and its performance in terms of the angle of the side mirrors at the same time and working time on the amount of energy absorbed was investigated by response surface methodology (RSM). The total amount of solar radiation as a measure of energy intake and increased water temperature inside the container was taken as an indicator of the amount of energy absorbed. The model on the basis of response surface methodology was used to validate the test and had a good validation (R2=0.89, R2adjusted=0.74 and lack of fit: no significant). Analyzing the results of a mathematical model was obtained for investigation of the effect of the side mirrors angle and time on the performance of the system. The amount of absorbed energy by theory and laboratory has been also compared and the average of error at all tests was 2.75%. Based on this model in the optimal condition, energy absorption was increased by 22.56%. This study was done at Institute of Food Science and Technology located in Mashhad with latitude 54 and 36 degrees and a height of 985 meters above sea level.

Abstract: Fuzzy DEA methods have been introduced to deal with the fuzziness of variables. Although, some of these variables are affected by uncertainty and also information granularity, the membership function of fuzzy set is certain and this contrasts with the fuzzy concept as a whole. Type-2 fuzzy sets are introduced because of this and their membership functions have the nature of fuzzy type-1. The calculations of type-2 fuzzy sets are very complicated. However, interval type-2 fuzzy sets which have the characteristics of type-2 fuzzy sets and do not add any complexity to the calculation process can be applied to deal with such a problem. That is why in this paper, it is explored that how an extension of interval type-2 fuzzy dynamic network DEA approach helps to measure airports’ sustainability. Sustainable airports play an irrefutable role in making transportation systems sustainable. Such an integrative approach in DEA models is unprecedented. So, this extension of DEA is valuable from both technical and conceptual aspects. Introduction: Airports are an essential component of aviation (Knudsen, 2004). The importance of airports becomes clearer when it comes to the fact that aviation traffic is more than before and, therefore, sustainability becomes difficult. While, various studies have suggested that the sustainability of airports is essential to improve the performance of these systems, improve the living conditions of the public and increase the airport's credit (Brian, 2005; ICAO, 2012; SAGA, 2015). Paying attention to the concept of sustainability in managing airports has various benefits, such as increased competitiveness by purifying activities, reducing operating costs, and reducing costs for life cycle of materials and equipment, better use of assets, utilization newer and better technologies, reducing asset development costs, getting more support from the community, improving working conditions and, as a result, improving employee productivity, reducing environmental risks, health, safety and promotion (SAGA, 2015; Bretzke, 2013; TRB, 2012; ACARE, 2011; Too, Earl, 2010). For the reasons mentioned, it can be said that it is necessary to pay attention to the sustainability of the passenger airports of the country. Certainly, before adopting any approach, the current situation must be assessed correctly. Various methods have been used to evaluate performance, but Data Envelopment Analysis (DEA) is one of the most widely used methods (Azizi et al., 2004). Data envelopment analysis is a functional and nonparametric method that allows consideration of various components as input and output or intermediate activities (Bray et al., 2015). However, no research has been found to determine the performance of airports in accordance with the principles of sustainability in Iran. Materials and Methods: Type-2 fuzzy Dynamic Data Envelopment Analysis (DEA) is used to assess the performance of Iran’s passenger airports based on sustainability development. By use of Dynamic Network Data Envelopment Analysis, one can see how the different parts of a decision unit can be linked. It also shows how the past performance of a decision-making unit can affect its current performance. In this type of data envelopment analysis, the function of the decision-making unit is transmitted through time-based intermediaries to the next period. Thus via using dynamic data envelopment analysis method, it is possible to consider the activities of different parts of a decision unit and also the efficiency with respect to time periods. However, the point is that in the real world, due to the increasing socioeconomic complexity and the inherent ambiguity of human thinking, there is no possibility of precise determination of many of the components. For this reason, type-2 fuzzy theory is employed that its membership function is the fuzzy of the first type. Since the complexity of calculations while using type-2 fuzzy set is high, interval type-2 fuzzy is applied. The 20 most popular passenger airports in Iran are selected to evaluate their performance in accordance with the principles of sustainability principles and via the help of the developed DEA model. Results and Discussion: Results of investigation show that Larestan Airport is the most efficient one among all and the last rank is allocated to the Isfahan airport considering fixed return to scale while in variable return to scale, Shiraz airport gets the last rank. The efficiency intervals of airports such as Larestan, Gorgan, Rasht and Yazd have little difference in two modes of return to scale. For this reason, we can say that there is no significant function inefficiency about these airports. But this difference is more evident in the efficiency of airports such as Mashhad. Airports, whose performance is generally low or are inefficient, are able to provide a groundbreaking improvement with appropriate benchmarking. Since airports operate in different conditions, difference in climatic conditions and the in workforce etc. should be considered while benchmarking. References ACARE (Advisory Council for Aeronautics Research in Europe) (2011). "Flight path 2050 Europe’s Vision for Aviation". Luxembourg: Publications Office of the European Union. Azizi, H., Kordrostami, S., & Amirteimoori, A. (2015). "Slacks-based measures of efficiency in imprecise data envelopment analysis: An approach based on data envelopment analysis with double frontiers". Computers & Industrial Engineering, 79, 42-51. Azizi, H., Jafari Shaerlar, A., & Farzipoor Saen, R. (2014). "A new Approach for Considering a Dual-Role Factor in Supplier Selection Problem: DEA with efficient and inefficient frontiers". Journal of production and operation management. 6(2), 129-144. Bray, S., Caggiani, l., & Ottomanelli, M. (2015). "Measuring transport systems efficiency under uncertainty by fuzzy sets theory based Data Envelopment Analysis: theoretical and practical comparison with traditional DEA model". Transportation Research Procedia, 5, 186 – 200. Bretzke, W.R. (2013). "Service Quality Versus Sustainability: A New Conflict of Objectives". Information Technology in Environmental Engineering Part of the series Environmental Science and Engineering, Springer, 179-190. Brian, E. (2005). "The Modern Airport Terminal: New Approaches to Airport Architecture". 2nd Edition, Taylor & Francis. ICAO (International Civil Aviation Organization) (2012). "Sustainable Future for Aviation: ICAO Rio+20 Global Initiative". http://climate-l.iisd.org/news/icao-publishes-booklet-for-rio20-decision makers (accessed 14.09.2015). Knudsen, F.B. (2004). "Defining Sustainability in the Aviation Sector". Brussell: Eurocontrol Experimental Centre. SAGA (Sustainable Aviation Guidance Alliance) (2015). "Learn". http://www.airportsustainability.org/learn, (accessed 16.12.2015). Transport Research Board (TRB) (2011). "Critical Issues in Aviation and the Environment 2011". Washington, DC: TRB. Too, L., & Earl, L. (2010). "Public transport service quality and sustainable development: a community stakeholder perspective". Sustainable Development. 18(1), 51-61.

Recently, the supply of electrical energy from sustainable and renewable energies such as mechanical, thermal and solar energy has been expanded. Piezoelectric materials are one of the best alternatives for supplying electrical energy from the mechanical energy available in nature such as mechanical force, vibration and human body movements. The applications for piezoelectric energy harvester include low power electronics or wireless sensing at relatively lower power levels (nW to mW) with an aim to reduce a reliance on batteries or electrical power through cables and realize fully autonomous and self-powered systems. In fact, the piezoelectric property is the property of a special material that enables the conversion of mechanical energy into electrical energy and vice versa. Piezoelectric property was discovered in ceramics for the first time. However, because of the need to piezoelectric materials with large surfaces and high flexibility in many applications, and the relatively low price and simple manufacturing technology of polymers in comparison with ceramics, polymers are used extensively. Poly(vinylidene fluoride) (PVDF) is a semicrystalline polymer with ferroelectric and piezoelectric properties. It has five distinctive configurations. β-phase is a polar phase showing significant piezoelectricity and pyroelectricity due to the highest dipolar moment and spontaneous polarization. In this review, PVDF polymer is introduced and then the different strategies for identification and quantification of PVDF phases are summarized. Finally, various methods including stretching, high pressure, ultra-fast cooling, melt quenching, using polar solvents, poling, copolymerization, polymer blending, electrospinning and filler addition such as carbon nanotube, clay, metals and metal salts, ceramics and etc., have been discussed for β-phase enhancement.

Introduction: The latest report of the Intergovernmental Panel on Climate Change (IPCC) states that future emissions of greenhouse gases (GHGs) will continue to increase and cause climatic change (16). These conditions are also true for Iran. The three greenhouse gases associated with agriculture are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). The three GHGs associated with agriculture CO2, CH4, and N2O differ in their effectiveness in trapping heat and in their turnover rates in the atmosphere. This environmental change will have serious impacts on different growth and development processes of crops. Increasing temperature could affect physiological processes such as photosynthesis, respiration and partitioning of photoassimilates. Farmers are not able to change or manage the climatic conditions, but some factors such as soil, water, seed and agricultural practices can be managed to reduce the adverse impacts of climate change (32). Mitigation and adaptation are two known ways for reducing the negative impacts of climate change. Mitigation strategies are associated with decreasing greenhouse gas (GHG) emissions through management practices such as reducing chemical fertilizer application, mechanization, increasing carbon storage in agroecosystems, planting biofuel crops and moving towards organic farming (42), etc. Material and Methods: This study was carried out at the experimental field of the Ferdowsi University of Mashhad in 2011 and was repeated in 2012. The Research Station (36°16´N, 59°36´E) is located at about 985 m a.s.l. Average temperature and precipitation rate of the research station in two years are shown in Figure. 1. The three-factor experiment was set up in a strip-split-plot arranged in a randomized complete block design with three replications. The experimental treatments were tillage systems (conventional and reduced tillage) and residual management (remaining and leaving of maize residual) assigned to main plots and different levels of N fertilizer (0, 150, 300 and 450 kg urea ha-1) was randomized as a subplot in tillage treatment. The seedbed preparation was made based on common practices at the location. Plot size under the trial was 4 m × 3 m so as to get 70 cm inter row spacing. Maize seeds (single-cross 704 cultivar) were hand sown in May for two years. The ideal density of the crops was considered as spacing 20 cm inter plant. As soon as the seeds were sown, irrigation continued every 10 days. No herbicides or chemical fertilizers were applied during the course of the trials and weeding was done manually when necessary. Measurement of CO2 emissions was performed by the closed chamber method. For this purpose, PVC plastic rings (20 cm in diameter and 30 cm height) were scattered on each of the plots. The chambers were placed in soil for two hours and the gathered air was collected by 10 ml vacuum syringe. Then, the samples were transferred to the laboratory and CO2 was measured using GC-mass. Results and Discussion: The results showed that CO2 emissions for conventional tillage was about 15 and 10% higher than the reduced tillage in 2011 and 2012, respectively. The CO2 emissions can be taken as indicators of soil tillage effects on the soil ecosystem, because CO2 emissions are closely connected to the microbial turnover and the physical accessibility of organic matter to microbes. These parameters were more available in the conventional tillage than the reduced tillage. CO2 emissions were strongly higher in the remaining residual condition rather than leaving condition in two years. CO2 emissions in the remaining residual condition was about 4.36 and 5.37 times higher than that of the leaving residual condition in 2011 and 2012, respectively. The microbial respiration and humidity of soil in the remaining residual condition is higher than that of the leaving residual condition. CO2 emission was elevated with increasing the rate of N fertilizer. The N fertilizer can increase the microbial activity of the soil. Cover cropping and N fertilization can increase CO2 emissions in full and reduced tilled soils by increasing the amount of crop residue returned to the soil. The results showed that CO2 emissions in 2011 were higher than 2012 in all treatments. The residual treatment had more effect on daily CO2 emission in comparison with tillage and N fertilizer treatments in both years. The trait was higher under conventional tillage, residue remaining and higher N fertilizer levels compared to reduced tillage, residue leaving and lower N fertilizer application. Linear regression for air temperature and mean CO2 emission illustrated that there was a positive correlation between air temperature and CO2 emission. Conclusion: In essence, the results showed that CO2 emissions for conventional tillage were higher than that of reduced tillage in two years. Remaining residual condition had strongly higher CO2 emission rather than leaving condition. CO2 emission was elevated with increasing the rate of N fertilizer.

In this research, By using data envelopment analysis method and output distance functions to decomposes energy productivity change into four components; technical efficiency change, technological change, changes in capital to energy ratio and labor in energy ratio In the industrial sector of the country Iran during the period 2014-2004. To this end, the output-axis data envelope analysis method has been used with the assumption of constant returns to scale. The results show that the effect of changing the ratio of capital to energy is a major factor in reducing the of energy intensity in the industrial sector of the Iran, changes technological progress, changes labor- energy ratio and changes technical efficiency drove up energy intensity in most industries.

Introduction In recent years human activities induced increases in atmospheric carbon dioxide (CO2). Increases in [CO2] caused global warming and Climate change. Climate change is anticipated to cause negative and adverse impacts on agricultural systems throughout the world. Higher temperatures are expected to lead to a host of problems. On the other hand, increasing of [CO2] anticipated causing positive impacts on crop yield. Considering the socio-economic importance of agriculture for food security, it is essential to undertake assessments of how future climate change could affect crop yields, so as to provide necessary information to implement appropriate adaptation strategies. In this perspective, the aim of this study was to assess potential climate change impacts and on production for one of the most important varieties of wheat (chamran) in Khouzestan plain and provide directions for possible adaptation strategies. Materials and Methods: For this study, The Ahvaz region located in the Khuzestan province of Iran was selected. Ahvaz has a desert climate with long, very hot summers and mild, short winters. At first, thirteen GCM models and two greenhouse gases emission (GHG) scenarios (A2 and B1) was selected for determination of climate change scenarios. ∆P and ∆T parameters at monthly scale were calculated for each GCM model under each GHG emissions scenario by following equation: Where ∆P, ∆T are long term (thirty years) precipitation and temperature differences between baseline and future period, respectively. average future GCM temperature (2015-2044) for each month, , average baseline period GCM temperature (1971-2000) for each month, , average future GCM precipitation for each month, , average baseline period GCM temperature (1971-2000) for each month and i is index of month. Using calculated ∆Ps for each month via AOGCM models and Beta distribution, Cumulative probability distribution function (CDF) determined for generated ∆Ps. ∆P was derived for risk level 0.10 from CDF. Using the measured precipitation for the 30 years baseline period (1971-2000) and LARS-WG model, daily precipitation time series under risk level 0.10 were generated for future periods (2015-2045 and 2070-2100). Mentioned process in above was performed for temperature. Afterwards, wheat growth was simulated during future and baseline periods using DSSAT, CERES-Wheat model. DSSAT, CERES4.5 is a model based on the crop growth module in which crop growth and development are controlled by phenological development processes. The DSSAT model contains the soil water, soil dynamic, soil temperature, soil nitrogen and carbon, individual plant growth module and crop management module (including planting, harvesting, irrigation, fertilizer and residue modules). This model is not only used to simulate the crop yield, but also to explore the effects of climate change on agricultural productivity and irrigated water. For model validation, field data from different years of observations were used in this study. Experimental data for the simulation were collected at the experimental farm of the Khuzestan Agriculture and Natural Resources Research Center (KANRC), located at Ahwaz in south western Iran. Results and Discussion: Results showed that wheat growth season was shortened under climate change, especially during 2070-2100 periods. Daily evapotranspiration increased and cumulative evapotranspiration decreased due to increasing daily temperatures and shortening of growth season, respectively. Comparing the wheat yield under climate change with base period based on the considered risk value (0.10) showed that wheat yield in 2015-2045 and 2070-2100 was decreased about 4 and 15 percent, respectively. Four adaptation strategies were assessed (shifting in the planting date, changing the amount of nitrogenous fertilizer, irrigation regime and breeding strategies) in response to climate change. Results indicated that Nov, 21 and Dec, 11 are the best planting dates for 2015-2045 and 2070-2100, respectively. The late season varieties with heat-tolerant characteristic had higher yield in comparison with short and normal season varieties. It indicated that breeding strategy was an appropriate adaptation under climate change. It was also found that the amount of nitrogen application will be reduced by 20 percent in future periods. The increase and decease of one irrigation application (40mm) to irrigation regime of base period resulted in maximum yield for 2015-2045 and 2070-2100, respectively. But, reduction of two irrigation application (80mm) resulted in maximum water productivity (WPI). Conclusions In the present study, four adaptation strategies of wheat (shifting in the planting date, changing the amount of nitrogenous fertilizer, irrigation regime and breeding strategies) under climate change in Ahvaz region were investigated. Result showed that Nov, 21 and Dec, 11 were the best planting dates for 2015-2045 and 2070-2100, respectively. The late season varieties with heat-tolerant characteristic had higher yield in comparison with short and normal season varieties. It indicated that breeding strategy was an appropriate adaptation strategy under climate change. It was also found that the amount of nitrogen application will be reduced by 20 percent in future periods. The increase and decease of one irrigation application (40mm) to irrigation regime of base period resulted in maximum yield for 2015-2045 and 2070-2100, respectively.

The main purpose of this paper is to determine the amount of subsidy required to promote the share of renewable energy in total electricity production. To do so, different scenarios have been studied by a hybrid approach of Computable General Equilibrium model. The results have been created by entering the details of technology-specific information for electricity generation into this model. The result of codification and calibration of the model shows that in the case of applying same subsidy to achieve 10 present shares of renewable energies in total electricity production, there is a need for 851 percent subsidy rate. Although in this case the wind energy is the only activated resource and the solar and biogas sections have not succeeded in achieving any rise in production rate. The other scenario was based on the unequal subsidy, proportional to disadvantage of different renewable energy. The result shows that, to achieve a balance growth of 4 percent energy productions from renewable sources, the rate of subsidy for wind energy should be 887 present. This rate for solar is 1776 present and for biogas is 1585 present. So, in the first scenario, the proper tariff for purchase of electricity from renewable energy is 4100 Rials per kWh. This tariff in the second scenario is 4260, 8520 and 7600 Rials per kWh respectively.

IntroductionThe problem of energy efficiency is one of the key pillars of economics, especially agricultural sector. In term of energy efficiency, a similar estimation for human actions and their consequents can be applied to the landscape system, which first introduced by Hall et al. (1986), and now referred to Energy Return on Investment (EROI). Many energy analyzes have been done, take into account a social system boundary and an input and output approach. This approach will inevitably hide the system's internal performance inside a black box. Recently, Tello et al. (2016) have proposed a novel approach for analyzing energy at the agricultural landscape scale with the aim of evaluating energy sustainability under multiple EROIs that views the landscape as a set of energy cycles between nature and society.The proposes of this study have been to consideration the theory and methodology of multiple EROIs, to investigate the efficiency of energy flow in Qazvin agricultural landscape and, to examine the relationship between energy efficiency and landscape heterogeneity in order to describe the interaction of landscape structure and energy efficiency.Materials and MethodsThe database of this case study was prepared from 46 counties of Agricultural Organization of Iran and land use map. Agricultural database was created based on agriculture, livestock, and pasture subsystems. Agricultural yield for each crop, number of agricultural, and horticultural labors, number and type of agricultural machinery, amount of fertilizers, herbicides and fungicides, used fossil fuels, electricity, and agricultural waste belonged to the agricultural sub-sector. Census of livestock, livestock and poultry production, livestock and poultry feed, livestock and poultry production, workers and machinery, fossil fuel and electricity needed and livestock waste were collected for the livestock sector. Pasture production used for livestock grazing, amount of livestock manure going back to rangelands were belong to pasture sector.All energy flows were converted to gross caloric value following research by Guzmán et al. (2014). In this method, the calculation of multiple EROIs has replaced the conventional methods of energy efficiency calculation. Landscape heterogeneity calculated using landscape metrics. Correlation coefficient was performed using SPSS between EROIs and heterogeneity.Results and DiscussionThe highest value of FEROI was found in Bashariyate Sharghi with 0.25 and the lowest was in Kharghane Gharbi with 0.018. EFEROI, which is the most similar to the conventional method of energy efficiency, had the highest rate with 0.666 in Bashariate Gharbi and the lowest rate with 0.020 in Kharqan Gharbi. IFEROI was 0.95 in Narjah and the lowest was in Shahidabad with 0.168. Lower IFEROI indicates a higher return biomass in the production system, which seeks to maintain reproduction in the system by closing the biophysical cycles. The highest NPPEROI were reported by Bashariate Gharbi at 1.122 and lowest by Kharqan Gharbi at 0.173.In this study the relationship between the EROIs index and the heterogeneity of the landscape structure was shown. The results have showed the inverse correlation between heterogeneity and energy efficiency, indicating the heterogeneous impact of landscape structure on these indicators. It can be deduced that the heterogeneity created by human in Qazvin province has reduced energy efficiency. To explain this inverse correlation between energy efficiency and the heterogeneity of the landscape, it should be noted that one of the factors affecting efficiency is that may final production come from land uses that needed more input energy and produce less output. By examining the relationship between these indices with land use and land cover of each county, it was found that these indices had their lowest level in dry farming. It means that in Qazvin province, energy efficiency in dry farming is low, and relay on external inputs, which was mainly fossil fuel.ConclusionThis study has explained how the calculation of several energy efficiency coefficients provides more complete information than conventional methods for decision making. The results of this study can be applied in land use planning to integrate energy considerations in planning and comprehensive agricultural development plan.